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dc.contributor.authorFoley, Louise
dc.contributor.authorDumuid, Dorothea
dc.contributor.authorAtkin, Andrew
dc.contributor.authorWijndaele, Katrien
dc.contributor.authorOgilvie, David
dc.contributor.authorOlds, Timothy
dc.date.accessioned2019-06-17T23:30:15Z
dc.date.available2019-06-17T23:30:15Z
dc.date.issued2019
dc.identifier.issn1932-6203
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/293651
dc.description.abstractBACKGROUND: Active living approaches seek to promote physical activity and reduce sedentary time across different domains, including through active travel. However, there is little information on how movement behaviours in different domains relate to each other. We used compositional data analysis to explore associations between active commuting and patterns of movement behaviour during discretionary time. METHODS AND FINDINGS: We analysed cross-sectional and longitudinal data from the UK Biobank study. At baseline (2006-2010) and follow up (2009-2013) participants reported their mode of travel to work, dichotomised as active (walking, cycling or public transport) or inactive (car). Participants also reported activities performed during discretionary time, categorised as (i) screen time; (ii) walking for pleasure; and (iii) sport and do-it-yourself (DIY) activities, summed to produce a total. We applied compositional data analysis to test for associations between active commuting and the composition and total amount of discretionary time, using linear regression models adjusted for covariates. Adverse events were not investigated in this observational analysis. The survey response rate was 5.5%. In the cross-sectional analysis (n = 182,406; mean age = 52 years; 51% female), active commuters engaged in relatively less screen time than those who used inactive modes (coefficient -0.12, 95% confidence interval [CI] -0.13 to -0.11), equating to approximately 60 minutes less screen time per week. Similarly, in the longitudinal analysis (n = 4,323; mean age = 51 years; 49% female) there were relative reductions in screen time in those who used active modes at both time points compared with those who used inactive modes at both time points (coefficient -0.15, 95% confidence interval [CI] -0.24 to -0.06), equating to a difference between these commute groups of approximately 30 minutes per week at follow up. However, as exposures and outcomes were measured concurrently, reverse causation is possible. CONCLUSIONS: Active commuting was associated with a more favourable pattern of movement behaviour during discretionary time. Active commuters accumulated 30-60 minutes less screen time per week than those using inactive modes. Though modest, this could have a cumulative effect on health over time.
dc.description.sponsorshipLF was funded by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged (087636/Z/08/Z, ES/G007462/1, MR/K023187/1). DO (MC_UU_12015/6) and KW (MC_UU_12015/3) were supported by the Medical Research Council.
dc.format.mediumElectronic-eCollection
dc.languageeng
dc.publisherPublic Library of Science (PLoS)
dc.rightsAll rights reserved
dc.subjectHumans
dc.subjectExercise
dc.subjectWalking
dc.subjectLinear Models
dc.subjectLongitudinal Studies
dc.subjectCross-Sectional Studies
dc.subjectBicycling
dc.subjectTravel
dc.subjectTransportation
dc.subjectAdult
dc.subjectAged
dc.subjectMiddle Aged
dc.subjectFemale
dc.subjectMale
dc.subjectSurveys and Questionnaires
dc.subjectUnited Kingdom
dc.subjectScreen Time
dc.subjectData Analysis
dc.subjectSedentary Behavior
dc.titleCross-sectional and longitudinal associations between active commuting and patterns of movement behaviour during discretionary time: A compositional data analysis.
dc.typeArticle
prism.issueIdentifier8
prism.publicationDate2019
prism.publicationNamePLoS One
prism.startingPagee0216650
prism.volume14
dc.identifier.doi10.17863/CAM.40763
dcterms.dateAccepted2019-04-25
rioxxterms.versionofrecord10.1371/journal.pone.0216650
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2019-01
dc.contributor.orcidFoley, Louise [0000-0003-3028-7340]
dc.contributor.orcidDumuid, Dorothea [0000-0003-3057-0963]
dc.contributor.orcidAtkin, Andrew [0000-0002-3819-3448]
dc.contributor.orcidWijndaele, Katrien [0000-0003-2199-7981]
dc.contributor.orcidOgilvie, David [0000-0002-0270-4672]
dc.contributor.orcidOlds, Timothy [0000-0001-6894-5519]
dc.identifier.eissn1932-6203
rioxxterms.typeJournal Article/Review
pubs.funder-project-idMedical Research Council (MR/K023187/1)
pubs.funder-project-idMedical Research Council (MC_UU_12015/6)
pubs.funder-project-idWellcome Trust (087636/Z/08/Z)
pubs.funder-project-idEconomic and Social Research Council (ES/G007462/1)
pubs.funder-project-idMedical Research Council (MC_UU_12015/3)
cam.issuedOnline2019-08-16
cam.orpheus.successMon Jun 08 08:19:04 BST 2020 - The item has an open VoR version.
rioxxterms.freetoread.startdate2022-06-17


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